Confidence polytopes for quantum process tomography

Abstract In the present work, we propose a generalization of confidence polytopes approach for quantum state tomography (QST) to case process (QPT). Our allows obtaining region in polytope form Choi matrix an unknown channel based on measurement results corresponding QPT experiment. The method uses improved version expression levels several positive operator-valued measures. We then demonstrate how can be employed calculating intervals affine functions states (Choi matrices), such as fidelities and observables mean values, which are used both QST settings. As propose, this problem efficiently solved using linear programming tools. also study performance scalability developed basis simulation experimental data collected IBM cloud processor.